mlflow

MLflow docs require manually downloading win-quality.csv.

r2d3

The r2d2 package docs require downloading flare.csv.

readr

The readr package docs require downloading challenge.csv.

Reproducible?

Download File

data_url <- paste0("https://raw.githubusercontent.com/",
                   "rstudio/r2d3/master/vignettes/gallery/",
                   "bubbles/flare.csv")

download.file(data_url)

Avoid Redownloading?

if (!file.exists("flare.csv")) {
  download.file(data_url, "flare.csv")
}

Support URL’s in all packages?

readr::read_csv(data_url)

# A tibble: 252 x 2
   id                                           value
   <chr>                                        <dbl>
 4 flare.analytics.cluster.AgglomerativeCluster  3938
 5 flare.analytics.cluster.CommunityStructure    3812
 6 flare.analytics.cluster.HierarchicalCluster   6714

Enough?

• Add to .gitignore?
• Share across projects?
• Detect upstream changes?
• Update or share datasets?

Cache

With pins we can easily cache resource,

pins::pin(data_url)

"/Users/javierluraschi/Library/Caches/pins/local/flare/flare.csv"

But wait, there is more!

Intro

Functionality

You can use the pins package to:

• Pin remote resources locally to work offline and cache results with ease, pin() stores resources in boards which you can then retrieve with pin_get().
• Discover new resources across different boards using pin_find().
• Share resources on GitHub, Kaggle or RStudio Connect by registering new boards with board_register().
• Resources can be anything from CSV, JSON, or image files to arbitrary R objects.

What can I pin?

Anything!

pins::pin(data_url)

pins::pin(mtcars)

pins::pin(lm(mpg ~ ., mtcars))

Where can I store pins?

Anywhere! – That implements the ‘board’ interface.

library(pins)
board_register(board = "local", name = "local")

pin(data_url, board = "local")

What is a board?

A storage location, like your local file systems, GitHub, Kaggle or RStudio Connect.

Pin

Discover

Share

Resources

Automation